Our preliminary studies using inbred mice show that mammalian genomes contain extensive, regional domains of functionally related elements that coalesced over evolutionary time to promote the coinheritance and survival of compatible sets of alleles at functionally related genes, and that domains on separate chromosomes interact in a distinctly non-random manner, forming scale-free networks. In effect, the mammalian genome is a dynamic system which varies spatially in its organization and expression and temporally in its evolution and inheritance. Using a team of computational biologists, molecular biologists and geneticists, we propose extending our studies of genome dynamics as an integrated system from an evolutionary perspective. This requires using computational approaches on large data sets we will generate to describe the interactions between genome organization, gene expression, phenotype determination and the impact of recombination hotspots in determining inheritance of co-adapted sets of alleles. By developing detailed maps of these interactions we can evaluate the underlying principles. We will develop training and outreach programs to make our information and tools available to the research community at large and initiate efforts to promote the development of this research area, taking advantage of The Jackson Laboratory's sustained programs in related efforts. To promote the long-term growth of this field of endeavor, in addition to the established faculty that have come together to pursue this program, we are recruiting several younger faculty so that their related efforts can flourish and develop over time. Our projects are designed to enhance our research capabilities for discovering the molecular mechanisms underlying human health and disease. Recent advances in genomic sciences have made it clear that reaching these understandings is a powerful step forward in developing improved prevention and therapy for our most common ills, including cancer, heart disease, and disorders of the immune and neurological systems.